Learning Experiences

I apologize for my brief hiatus – it’s been almost two weeks since I’ve posted. I have been very busy recently, but for a very exciting reason: I got a job as a summer student of Dr. Steve Easterbrook! You can read more about Steve and his research on his faculty page and blog.

This job required me to move cities for the summer, so my mind has been consumed with thoughts such as “Where am I and how do I get home from this grocery store?” rather than “What am I going to write a post about this week?” However, I have had a few days on the job now, and as Steve encourages all of his students to blog about their research, I will use this outlet to periodically organize my thoughts.

I will be doing some sort of research project about climate modelling this summer – we’re not yet sure exactly what, so I am starting by taking a look at the code for some GCMs. The NCAR Community Earth System Model is one of the easiest to access, as it is largely an open source project. I’ve only read through a small piece of their atmosphere component, but I’ve already seen more physics calculations in one place than ever before.

I quickly learned that trying to understand every line of the code is a silly goal, as much as I may want to. Instead, I’m trying to get a broader picture of what the programs do. It’s really neat to have my knowledge about different subjects converge so completely. Multi-dimensional arrays, which I have previously only used to program games of Sudoku and tic-tac-toe, are now being used to represent the entire globe. Electric potential, a property I last studied in the circuitry unit of high school physics, somehow impacts atmospheric chemistry. The polar regions, which I was previously fascinated with mainly for their wildlife, also present interesting mathematical boundary cases for a climate model.

It’s also interesting to see how the collaborative nature of CESM, written by many different authors and designed for many different purposes, impacts its code. Some of the modules have nearly a thousand lines of code, and some have only a few dozen – it all depends on the programming style of the various authors. The commenting ranges from extensive to nonexistent. Every now and then one of the files will be written in an older version of Fortran, where EVERYTHING IS IN UPPER CASE.

I am bewildered by most of the variable names. They seem to be collections of abbreviations I’m not familiar with. Some examples are “mxsedfac”, “lndmaxjovrdmdni”, “fxdd”, and “vsc_knm_atm”.

When we get a Linux machine set up (I have heard too many horror stories to attempt a dual-boot with Windows) I am hoping to get a basic CESM simulation running, as well as EdGCM (this could theoretically run on my laptop, but I prefer to bring that home with me each evening, and the simulation will probably take over a day).

I am also doing some background reading on the topic of climate modelling, including this book, which led me to the story of PHONIAC. The first weather prediction done on a computer (the ENIAC machine) was recreated as a smartphone application, and ran approximately 3 million times faster. Unfortunately, I can’t find anyone with a smartphone that supports Java (argh, Apple!) so I haven’t been able to try it out.

I hope everyone is having a good summer so far. A more traditional article about tornadoes will be coming at the end of the week.


Academic Culture From the Inside – a Guest Post by Steve Easterbrook

Steve Easterbrook is a comp-sci professor at the University of Toronto who has also worked at the University of Sussex and NASA. Recently, he decided to apply his software engineering expertise to the challenge of climate change, particularly relating to climate models.

This post began as a comment on a recent RealClimate post about media coverage of the CRU hack. I liked it so much that I requested his permission to reprint it here. Enjoy!

I’m afraid to say that a lot of the personal emails between academics in any field are probably not very nice. We tend to be very blunt about what appears to us as ignorance, and intolerant of anything that wastes our time or distracts us from our work. And when we think (rightly or wrongly) that the peer review process has let another crap paper through, we certainly don’t hold back in expressing our opinions to one another.

Of course, this is completely different to how we behave when we meet one another. Most scientists seem able to distinguish clearly between the intellectual cut and thrust (in which we’re very rude about one another’s ideas) and social interactions (in which we all get together over a beer and bitch about the downsides of academic life). Occasionally, there’s someone who is unable to separate the two, and takes the intellectual jabs personally, but such people are rare enough in most scientific fields that the rest of us know exactly who they are, and try to avoid them at conferences!

Part of this is due to the nature of the academic research. We care deeply about intellectual rigor, and preserving the integrity of the published body of knowledge. But we also know that many key career milestones are dependent on being respected (and preferably liked) by others in the field, such as the more senior people who write recommendation letters for tenure and promotion and honors, or the scientists with competing theories who will get asked to peer review our papers, etc.

Most career academics have large egos and very thick skins. I think the tenure process and the peer review process filter out those who don’t. So, expect to see rudeness in private, especially when we’re discussing other scientists behind their backs with likeminded colleagues, coupled with a more measured politeness in public (e.g. at conferences).

Now, in climate science, all our conventions are being broken. Private email exchanges are being made public. People who have no scientific training and/or no prior exposure to the scientific culture are attempting to engage in a discourse with scientists, and these people just don’t understand how science works. The climate scientists whom they attempt to engage are so used to interacting only with other scientists (we live rather sheltered lives- they don’t call it the ivory tower for nothing) that they don’t know how to engage with these outsiders. What in reality is a political streetfight, we mistake for an intellectual discussion over brandy in the senior commonroom. Scientists have no training for this type of interaction, and so our responses look (to the outsiders)  rude, dismissive, and perhaps unprofessional.

Journalists like Monbiot, despite all his brilliant work in keeping up with the science and trying to explain it to the masses, just haven’t ever experienced academic culture from the inside. Hence his call, which he keeps repeating, for Phil Jones to resign, on the basis that Phil reacted unprofessionally to FOI requests. You don’t get data from a scientist by using FOI requests, you do it by stroking their ego a little, or by engaging them with a compelling research idea you want to pursue with it. And in the rare cases where this doesn’t work, you do the extra work to reconstruct it from other sources, or modify your research approach (because it’s the research we care about, not any particular dataset itself). So to a scientist, anyone stupid enough to try to get scientific data through repeated FOI requests quite clearly deserves our utter contempt. Jones was merely expressing (in private) a sentiment that most scientists would share – and extreme frustration with people who clearly don’t get it.

The same misunderstandings occur when outsiders look at how we talk about the peer-review process. We’re used to having our own papers rejected from time to time, and we learn how to deal with it – quite clearly the reviewers were stupid, and we’ll show them by getting it published elsewhere (remember, big ego, thick skin). We’re also used to seeing the occasional crap paper get accepted (even into our most prized journals), and again we understand that the reviewers were stupid, and the journal editors incompetent, and we waste no time in expressing that. And if there’s a particularly egregious example, everyone in the community will know about it, everyone will agree it’s bad, and some will start complaining loudly about the editor who let it through.

Yet at the same time, we’re all reviewers, so it’s understood that the people we’re calling stupid and incompetent are our colleagues. And a big part of calling them stupid or incompetent is to get them to be more rigorous next time round, and it works because no honest scientist wants to be seen as lacking rigor. What looks to the outsider like a bunch of scientists trying to subvert some gold standard of scientific truth is really just scientists trying to goad one another into doing a better job in what we all know is a messy, noisy process.

The bottom line is that scientists will always tend to be rude to ignorant and lazy people, because we expect to see in one another a driving desire to master complex ideas and to work damn hard at it. Unfortunately the outside world (and many journalists) interpret that rudeness as unprofessional conduct. And because they don’t see it every day (like we do!) they’re horrified.